TY - GEN
T1 - Investigation of Different Conditions to Detect Cycles in Linearly Implicit Quantized State Systems
AU - Elbellili, Elmongi
AU - Lauwens, Ben
AU - Huybrechs, Daan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The increasing complexity of modern engineering systems presents a challenge to the digital simulation of these systems which usually can be represented by differential equations. The Linearly Implicit Quantized State System (LIQSS) offers an alternative approach to traditional numerical integration techniques for solving Ordinary Differential Equations (ODEs). This method proved effective for handling discontinuous and large stiff systems. However, the inherent discrete nature of LIQSS may introduce oscillations that result in unnecessary computational steps. The current oscillation detection mechanism relies on a condition that checks the significance of the derivatives, but it could be further improved. This paper describes a different cycle detection mechanism and presents the outcomes using LIQSS order one in simulating the Advection Diffusion problem. The efficiency of this new cycle detection mechanism is verified by comparing the performance of the current solver against the new version as well as a reference solution using a Runge-Kutta method of order14.
AB - The increasing complexity of modern engineering systems presents a challenge to the digital simulation of these systems which usually can be represented by differential equations. The Linearly Implicit Quantized State System (LIQSS) offers an alternative approach to traditional numerical integration techniques for solving Ordinary Differential Equations (ODEs). This method proved effective for handling discontinuous and large stiff systems. However, the inherent discrete nature of LIQSS may introduce oscillations that result in unnecessary computational steps. The current oscillation detection mechanism relies on a condition that checks the significance of the derivatives, but it could be further improved. This paper describes a different cycle detection mechanism and presents the outcomes using LIQSS order one in simulating the Advection Diffusion problem. The efficiency of this new cycle detection mechanism is verified by comparing the performance of the current solver against the new version as well as a reference solution using a Runge-Kutta method of order14.
KW - Cycle Detection
KW - Numerical Integration
KW - Ordinary Differential Equations
KW - Quantized State Systems
KW - Stiffness
UR - http://www.scopus.com/inward/record.url?scp=85203690560&partnerID=8YFLogxK
U2 - 10.1109/ICCMSO61761.2024.00095
DO - 10.1109/ICCMSO61761.2024.00095
M3 - Conference contribution
AN - SCOPUS:85203690560
T3 - Proceedings - 2024 3rd International Conference on Computational Modelling, Simulation and Optimization, ICCMSO 2024
SP - 469
EP - 473
BT - Proceedings - 2024 3rd International Conference on Computational Modelling, Simulation and Optimization, ICCMSO 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Computational Modelling, Simulation and Optimization, ICCMSO 2024
Y2 - 14 June 2024 through 16 June 2024
ER -